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Mon, 03 Apr 2000 00:00:00 +0200Mon, 03 Apr 2000 00:00:00 +0200An Evaluation of the INRECA CBR Systemhttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/131
We present an approach to systematically describing case-based reasoning systems bydifferent kinds of criteria. One main requirement was the practical relevance of these criteria and their usability for real-life applications. We report on the results we achieved from a case study carried out in the INRECA1 Esprit project.Klaus-Dieter Althoff; Karl-Heinz Weisarticlehttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/131Mon, 03 Apr 2000 00:00:00 +0200Induction and Case-Based Reasoning for Classification Taskshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/132
We present two techniques for reasoning from cases to solve classification tasks: Induction and case-based reasoning. We contrast the two technologies (that are often confused) and show how they complement each other. Based on this, we describe how they are integrated in one single platform for reasoning from cases: The Inreca system.Klaus-Dieter Althoffarticlehttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/132Mon, 03 Apr 2000 00:00:00 +0200Fallbasiertes Schliessen in Expertensystemen: Welche Rolle spielen Fälle für wissensbasierte Systeme?https://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/108
Fallbasiertes Schliessen ist ein derzeit viel diskutierter Problemlösesansatz. Dieser Beitrag gibt einen Überblick über den aktuellen Stand der Forschung auf diesem Gebiet, insbesondere im Hinblick auf die Entwicklung von Expertensystemen (einen ersten Schritt in diese Richtung stellte bereits der Beitrag von Bartsch-Spörl, [BS87] dar). Dazu stellen wir die dem fallbasierten Schliessen zugrundeliegenden Mechanismen vor. Ergänzt wird dies durch den Vergleich mit alternativen Verfahren wie z.B. regelbasiertes, analoges und induktives Schliessen sowie eine ausführliche Literaturübersicht.Klaus-Dieter Althoff; Stefan Wess; Brigitte Bartsch-Spörl; Dietmar Janetzko; Frank Maurer; Angi Vosspreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/108Mon, 03 Apr 2000 00:00:00 +0200Fallbasiertes Schliessen zur Kreditwürdigkeitsprüfunghttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/111
In diesem Artikel diskutieren wir Anforderungen aus der Kreditwürdigkeitsprüfung und ihre Erfüllung mit Hilfe der Technik des fallbasierten Schliessens. Innerhalb eines allgemeinen Ansatzes zur fallbasierten Systementwicklung wird ein Lernverfahren zur Optimierung von Entscheidungskosten ausführlich beschrieben. Dieses Verfahren wird, auf der Basis realer Kundendaten, mit dem fallbasierten Entwicklungswerkzeug INRECA empirisch bewertet. Die Voraussetzungen für den Einsatz fallbasierter Systeme zur Kreditwürdigkeitsprüfung werden abschliessend dargestellt und ihre Nüt zlichkeit diskutiert.Wolfgang Wilke; Ralph Bergmann; Klaus-Dieter Althoffpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/111Mon, 03 Apr 2000 00:00:00 +0200Methodology for Building CBR Applicationshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/120
As the previous chapters of this book have shown, case-based reasoning is a technology that has been successfully applied to a large range of different tasks. Through all the different CBR projects, both basic research projects as well as industrial development projects, lots of knowledge and experience about how to build a CBR application has been collected. Today, there is already an increasing number of successful companies developing industrial CBR applications. In former days, these companies could develop their early pioneering CBR applications in an ad-hoc manner. The highly-skilled CBR expert of the company was able to manage these projects and to provide the developers with the required expertise.Ralph Bergmann; Klaus-Dieter Althoffpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/120Mon, 03 Apr 2000 00:00:00 +0200Evaluating Case-Based Reasoning Systemshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/121
Evaluation is an important issue for every scientific field and a necessity for an emerging soft-ware technology like case- based reasoning. This paper is a supplementation to the review of industrial case-based reasoning tools by K.-D. Althoff, E. Auriol, R. Barletta and M. Manago which describes the most detailed evaluation of commercial case-based reasoning tools currently available. The author focuses on some important aspects that correspond to the evaluation ofcase-based reasoning systems and gives links to ongoing research.Klaus-Dieter Althoffpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/121Mon, 03 Apr 2000 00:00:00 +0200INRECA - A Seamless Integration of Induction and Case-Based Reasoning for Decision Support Taskshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/130
We propose an integrated approach to decision support and diagnostic problems based on top-down induction of decision trees (TDIDT) and case-based reasoning (CBR).Klaus-Dieter Althoff; Stefan Wess; Ralph Traphönerpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/130Mon, 03 Apr 2000 00:00:00 +0200INRECA - A Seamless Integration of Induction and Case-Based Reasoning for Decision Support Taskshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/139
We propose an integrated approach to decision support and diagnostic problems based on top-down induction of decision trees (TDIDT) and case-based reasoning (CBR).Klaus-Dieter Althoff; Stefan Wess; Ralph Traphönerpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/139Mon, 03 Apr 2000 00:00:00 +0200Case-Based Reasoning for Decision Support and Diagnostic Problem Solving: The INRECA Approachhttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/140
INRECA offers tools and methods for developing, validating, and maintaining decision support systems. INRECA's basic technologies are inductive and case-based reasoning, namely KATE -INDUCTION (cf., e.g., Manago, 1989; Manago, 1990) and S3-CASE, a software product based on PATDEX (cf., e.g., Wess,1991; Richter & Wess, 1991; Althoff & Wess, 1991). Induction extracts decision knowledge from case databases. It brings to light patterns among cases and helps monitoring trends over time. Case-based rea -soning relates the engineer's current problem to past experiences.Klaus-Dieter Althoffpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/140Mon, 03 Apr 2000 00:00:00 +0200Fallbasiertes Problemlösen in Expertensystemen begriffliche und inhaltliche Betrachtungenhttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/148
Im Bereich der Expertensysteme ist das Problemlösen auf der Basis von Fallbeispielen ein derzeit sehr aktuelles Thema. Da sich sehr unterschiedliche Fachgebiete und Disziplinen hiermit auseinandersetzen, existiert allerdings eine entsprechende Vielfalt an Begriffen und Sichten auf fallbasiertes Problemlösen. In diesem Beitrag werden wir einige für das fallbasierte Problemlösen wichtige Begriffe präzisieren bzw. begriffliche Zusammenhänge aufdecken. Die dabei verfolgte Leitlinie ist weniger die, ein vollständiges Begriffsgebäude zu entwickeln, sondern einen ersten Schritt in Richtung eines einfachen Beschreibungsrahmens zu gehen, um damit den Vergleich verschiedener Ansätze und Systeme zu ermöglichen. Auf dieser Basis wird dann der derzeitige Stand der Forschung am Beispiel konkreter Systeme zur fallbasierten Diagnose dargelegt. Den Abschluss bildet eine Darstellung bislang offener Fragen und interessanter Forschungsziele.Klaus-Dieter Althoff; Stefan Wesspreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/148Mon, 03 Apr 2000 00:00:00 +0200Using k-d Trees to Improve the Retrieval Step in Case-Based Reasoning?https://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/150
Retrieval of cases is one important step within the case-based reasoning paradigm. We propose an improvement of this stage in the process model for finding most similar cases with an average effort of O[log2n], n number of cases. The basic idea of the algorithm is to use the heterogeneity of the search space for a density-based structuring and to employ this precomputed structure, a k-d tree, for efficient case retrieval according to a given similarity measure sim. In addition to illustrating the basic idea, we present the expe- rimental results of a comparison of four different k-d tree generating strategies as well as introduce the notion of virtual bounds as a new one that significantly reduces the retrieval effort from a more pragmatic perspective. The presented approach is fully implemented within the (Patdex) system, a case-based reasoning system for diagnostic applications in engineering domains.Klaus-Dieter Althoff; Stefan Wess; Guido Derwandpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/150Mon, 03 Apr 2000 00:00:00 +0200Knowledge acquisition in the domain of CNC machining centers: the Moltke approachhttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/342
MOLTKE is a research project dealing with a complex technical application. After describing the domain of CNCmachining centers and the applied KA methods, we summarize the concrete KA problems which we have to handle. Then we describe a KA mechanism which supports an engineer in developing a diagnosis system. In chapter 6 weintroduce learning techniques operating on diagnostic cases and domain knowledge for improving the diagnostic procedure of MOLTKE. In the last section of this chapter we outline some essential aspects of organizationalknowledge which is heavily applied by engineers for analysing such technical systems (Qualitative Engineering). Finally we give a short overview of the actual state of realization and our future plans.Klaus-Dieter Althoff; S. Kockskämper; R. Traphöner; W. Wernickepreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/342Mon, 03 Apr 2000 00:00:00 +0200Multiple knowledge acquisition strategies in MOLTKEhttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/375
In this paper we will present a design model (in the sense of KADS) for the domain of technical diagnosis. Based on this we will describe the fully implemented expert system shell MOLTKE 3.0, which integrates common knowledge acquisition methods with techniques developed in the fields of Model-Based Diagnosis and Machine Learning, especially Case-Based Reasoning.Klaus-Dieter Althoff; Frank Maurer; Robert Rehboldpreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/375Mon, 03 Apr 2000 00:00:00 +0200Case-based knowledge acquisition, learning and problem solving for diagnostic real world taskshttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/408
Within this paper we focus on both the solution of real, complex problems using expert system technology and the acquisition of the necessary knowledge from a case-based reasoning point of view. The development of systems which can be applied to real world problems has to meet certain requirements. E.g., all available information sources have to be identified and utilized. Normally, this involves different types of knowledge for which several knowledge representation schemes are needed, because no scheme is equally natural for all sources. Facing empirical knowledge it is important to complement the use of manually compiled, statistic and otherwise induced knowledge by the exploitation of the intuitive understandability of case-based mechanisms. Thus, an integration of case-based and alternative knowledge acquisition and problem solving mechanisms is necessary. For this, the basis is to define the "role" which case-based inference can "play" within a knowledge acquisition workbench. We will discuss a concrete casebased architecture, which has been applied to technical diagnosis problems, and its integration into a knowledge acquisition workbench which includes compiled knowledge and explicit deep models, additionally.Klaus-Dieter Althoff; Stefan Wesspreprinthttps://kluedo.ub.uni-kl.de/frontdoor/index/index/docId/408Mon, 03 Apr 2000 00:00:00 +0200